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Item specifics

Condition
Very Good: A book that does not look new and has been read but is in excellent condition. No obvious …

ISBN
9789812560940
Publication Year
2005
Series
Series on Software Engineering and Knowledge Engineering
Type
Textbook
Format
Hardcover
Language
English
Subject Area
Computers
Publication Name
Machine Learning Applications in Software Engineering
Author
Jeffrey J. P. Tsai
Publisher
World Industries Scientific Publishing Co Pte LTD
Subject
Software Development & Engineering / General
Item Weight
0 Oz
Number of Pages
368 Pages

MACHINE LEARNING APPLICATIONS IN SOFTWARE ENGINEERING (Software Engineering and

About this product

Product Identifiers

Publisher
World Industries Scientific Publishing Co Pte LTD
ISBN-10
9812560947
ISBN-13
9789812560940
eBay Product ID (ePID)
43996139

Product Key Features

Number of Pages
368 Pages
Language
English
Publication Name
Machine Learning Applications in Software Engineering
Publication Year
2005
Subject
Software Development & Engineering / General
Type
Textbook
Subject Area
Computers
Author
Jeffrey J. P. Tsai
Series
Series on Software Engineering and Knowledge Engineering
Format
Hardcover

Dimensions

Item Weight
0 Oz

Additional Product Features

Intended Audience
Scholarly & Professional
Dewey Edition
22
Series Volume Number
Vol. 16
Volume Number
Vol. 16
Dewey Decimal
005.1
Synopsis
Machine learning deals with the issue of how to build computer programs that improve their performance at some tasks through experience. Machine learning algorithms have proven to be of great practical value in a variety of application domains. Not surprisingly, the field of software engineering turns out to be a fertile ground where many software development and maintenance tasks could be formulated as learning problems and approached in terms of learning algorithms. This book deals with the subject of machine learning applications in software engineering. It provides an overview of machine learning, summarizes the state-of-the-practice in this niche area, gives a classification of the existing work, and offers some application guidelines. Also included in the book is a collection of previously published papers in this research area.
LC Classification Number
QA76.758

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